In a paper, it mentioned: ANN, RNN, and LSTM NN are optimized to contain three hidden layers with 1000 hidden units in each layer.
I would like to model the RNN model in Keras. But my code fails in an error!
My code:
model=Sequential()
model.add(SimpleRNN(1000,input_shape=(320,15),activation='relu'))
model.add(SimpleRNN(1000))
model.add(SimpleRNN(1000))
model.add(Dense(1600))
Error:
ValueError Traceback (most recent call last)
<ipython-input-49-ff01ce62eb30> in <module>()
1 model=Sequential()
2 model.add(SimpleRNN(1000,input_shape=(320,15),activation='relu'))
----> 3 model.add(SimpleRNN(1000))
4 model.add(SimpleRNN(1000))
5 model.add(Dense(1600))
.....
....
...
..
.
ValueError: Input 0 is incompatible with layer simple_rnn_2: expected ndim=3, found ndim=2
How can I code for the RNN model which is optimized to contain three hidden layers with 1000 hidden units in each layer?
Thank you so much